# coffea.hist

Histogramming tools

coffea.hist is a histogram filling, transformation, and plotting sub-package, utilizing numpy arrays for storage and matplotlib plotting routines for visualization.

Features found in this package are similar to those found in packages such as histbook (deprecated), boost-histogram (in development), physt, and built-in numpy histogram utilities.

## Functions

 `poisson_interval`(sumw, sumw2[, coverage]) Frequentist coverage interval for Poisson-distributed observations `clopper_pearson_interval`(num, denom[, coverage]) Compute Clopper-Pearson coverage interval for a binomial distribution `normal_interval`(pw, tw, pw2, tw2[, coverage]) Compute errors based on the expansion of pass/(pass + fail), possibly weighted `plot1d`(hist[, ax, clear, overlay, stack, ...]) Create a 1D plot from a 1D or 2D `Hist` object `plotratio`(num, denom[, ax, clear, overflow, ...]) Create a ratio plot, dividing two compatible histograms `plot2d`(hist, xaxis[, ax, clear, xoverflow, ...]) Create a 2D plot from a 2D `Hist` object `plotgrid`(h[, figure, row, col, overlay, ...]) Create a grid of plots, enumerating identifiers on up to 3 axes `export1d`(hist) Export a 1-dimensional `Hist` object to uproot

## Classes

 `Hist`(label, *axes, **kwargs) Specify a multidimensional histogram. `Bin`(name, label, n_or_arr[, lo, hi]) A binned axis with name, label, and binning. `Interval`(lo, hi[, label]) Real number interval `Cat`(name, label[, sorting]) A category axis with name and label `StringBin`(name[, label]) A string used to fill a sparse axis

## Class Inheritance Diagram 